Uncertainpy: A Python Toolbox for Uncertainty Quantification and Sensitivity Analysis in Computational Neuroscience

Computational models in neuroscience typically contain many parameters that are poorly constrained by experimental data. Uncertainty quantification and sensitivity analysis provide rigorous procedures to quantify how the model output depends on this parameter uncertainty. Unfortunately, the applicat...

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Detalles Bibliográficos
Autores principales: Tennøe, Simen, Halnes, Geir, Einevoll, Gaute T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6102374/
https://www.ncbi.nlm.nih.gov/pubmed/30154710
http://dx.doi.org/10.3389/fninf.2018.00049

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6102374/
https://www.ncbi.nlm.nih.gov/pubmed/30154710
http://dx.doi.org/10.3389/fninf.2018.00049

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